Data Scientist I

Summary

Tavern Research is a political tech startup building tools and insights to help customers win elections and make better, evidence-based decisions. The Data Scientist I will work with messy data to clean, structure, and prepare it for analysis, contributing to modeling tasks and collaborating with senior team members.

Responsibilities

• Work hands-on with real-world, unstructured data: cleaning, debugging, and engineering features that support effective models
• Support the design and execution of numerical experiments by handling data prep, fitting models, and running standard analyses
• Contribute to feature engineering and model building, taking ownership of clearly defined components of modeling projects
• Write clean, well-documented Python code using standard data science libraries
• Assist with model evaluation, diagnostics, and performance monitoring
• Collaborate with researchers and engineers to scope and execute tightly defined tasks
• Learn and apply best practices and emerging tools in machine learning, AI, and causal inference

Skills

• This role is designed for early-career candidates with 0–3 years of experience or equivalent hands-on project work who are eager to grow into more advanced modeling responsibilities
• Strong academic or applied background in data science and software engineering or closely related fields
• Experience building statistical models (beyond differential equations or simulations)
• Demonstrated experience working with messy, real-world datasets
• Proficiency in Python and standard data science libraries
• Familiarity with AI and machine learning concepts like embeddings, supervised and unsupervised ML methods, and agentic systems
• Clear understanding of the data science concepts behind work you've done (not just 'I ran the code')
• Strong communication skills and a collaborative mindset
• Humility, patience, and attention to detail
• We especially value candidates who have independently built data or modeling projects outside of coursework, including internships, research, or production data work
• Bonus: exposure to model deployment, large language models, or causal inference

Qualifications

Must Haves

• This role is designed for early-career candidates with 0–3 years of experience or equivalent hands-on project work who are eager to grow into more advanced modeling responsibilities
• Strong academic or applied background in data science and software engineering or closely related fields
• Experience building statistical models (beyond differential equations or simulations)
• Demonstrated experience working with messy, real-world datasets
• Proficiency in Python and standard data science libraries
• Familiarity with AI and machine learning concepts like embeddings, supervised and unsupervised ML methods, and agentic systems
• Clear understanding of the data science concepts behind work you've done (not just 'I ran the code')
• Strong communication skills and a collaborative mindset
• Humility, patience, and attention to detail
• We especially value candidates who have independently built data or modeling projects outside of coursework, including internships, research, or production data work

Nice to Haves

• Bonus: exposure to model deployment, large language models, or causal inference

Benefits

• Premium health insurance
• Unlimited PTO
• Office closed for all federal holidays
• 401k match
• Equity